Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method comprising: detecting partial entry of a search query at the mobile computing device; accessing a location history of the mobile computing device; identifying, by a hardware processor, a predicted route of the mobile computing device based in part on the location history, the identifying comprising: accessing stored travel information of the mobile computing device between different locations in a geographic region; identifying one or more destination elements in the geographic region using the stored travel information; and determining probabilities that the one or more destination elements are a future location of the mobile computing device, the identifying being based at least on the probabilities; based on the location history, the predicted route, and the partial entry, determining a suggestion comprising one or more auto-complete search terms that complete the partial entry of the search query, the suggestion including a location along the predicted route; and causing presentation of the suggestion that includes the location to complete the partial entry of the search query on the mobile computing device.
A method enhances search query auto-completion on mobile devices by leveraging location history and predicted routes. The technology addresses the challenge of providing relevant search suggestions when users input partial queries, particularly for location-based searches. The method detects partial query input on a mobile device and accesses its location history to analyze travel patterns. Using stored travel information between different geographic locations, the system identifies potential destination elements and calculates probabilities that these destinations are future locations of the device. Based on the location history, predicted route, and partial query, the method generates auto-complete suggestions that include relevant locations along the predicted path. These suggestions are then presented to the user to complete the partial search query. The approach improves search efficiency by anticipating user intent based on historical movement data and contextual relevance.
2. The method of claim 1 , wherein the location along the predicted route comprises a predicted destination of the mobile computing device.
3. The method of claim 1 , wherein the one or more destination elements are identified based at least on being reachable from a current location of the mobile computing device within a predetermined amount of time in accordance with the stored travel times information.
4. The method of claim 1 , wherein the identifying the predicted route comprises using a Markov model.
A system and method for predicting a route of a vehicle involves analyzing sensor data to determine the vehicle's current position and movement patterns. The system identifies a predicted route by applying a Markov model, which evaluates probabilistic transitions between different road segments or locations based on historical or real-time data. The Markov model assigns probabilities to possible routes, allowing the system to select the most likely path the vehicle will follow. This approach helps in anticipating the vehicle's trajectory for applications such as collision avoidance, traffic management, or autonomous navigation. The system may also incorporate additional data, such as traffic conditions or road infrastructure, to refine the prediction. By using a probabilistic model, the system dynamically adapts to changing conditions and improves route prediction accuracy over time. The method is particularly useful in scenarios where precise route forecasting is critical for safety or efficiency, such as in autonomous driving or fleet management. The Markov model's ability to handle uncertainty and transitions between states makes it effective for real-world navigation challenges.
5. The method of claim 1 , further comprising: causing a search to be performed based on the search query including the location along the predicted route; and causing display of an interface at the mobile computing device that presents results of the search based on the search query including the location along the predicted route.
6. The method of claim 5 , further comprising: determining a speed of the mobile computing device based on the accessed location history; determining that the speed of the mobile computing device transgresses a threshold that indicates that a user of the mobile computing device is traveling on a highway; and in response to determining that the speed transgresses the threshold, prioritizing the results of the search that are associated with one or more exits on the highway.
7. The method of claim 5 , further comprising, in response to a user selection of one of the results, causing display of an information box on a portion of the interface that is presenting the results, the information box including information for the selected one of the results.
8. The method of claim 1 , further comprising based on the predicted route, pre-fetching content likely to be retrieved by a user of the mobile computing device in a subsequent search.
9. A system comprising: one or more hardware processors; and a storage device storing instructions that, when executed by the one or more hardware processors, cause the one or more hardware processors to perform operations comprising: detecting partial entry of a search query at the mobile computing device; accessing a location history of the mobile computing device; identifying a predicted route of the mobile computing device based in part on the location history; based on the location history, the predicted route, and the partial entry, determining a suggestion comprising one or more auto-complete search terms that complete the partial entry of the search query, the suggestion including a location along the predicted route; causing presentation of the suggestion that includes the location to complete the partial entry of the search query on the mobile computing device; causing a search to be performed based on the search query including the location along the predicted route; determining a speed of the mobile computing device based on the accessed location history; determining that the speed of the mobile computing device transgresses a threshold that indicates that a user of the mobile computing device is traveling on a highway; in response to determining that the speed transgresses the threshold, prioritizing results of the search that are associated with one or more exits on the highway; and causing display of an interface at the mobile computing device that presents the results of the search based on the search query.
10. The system of claim 9 , wherein the location along the predicted route comprises a predicted destination of the mobile computing device.
11. The system of claim 9 , wherein the identifying the predicted route comprises: accessing stored travel times of the mobile computing device between different locations in a geographic region; identifying one or more destination elements in the geographic region using the stored travel times; and determining probabilities that the one or more destination elements are a future location of the mobile computing device, wherein the identifying the predicted route of the mobile computing device is based at least on the probabilities.
12. The system of claim 11 , wherein the one or more destination elements are identified based at least on being reachable from a current location of the mobile computing device within a predetermined amount of time in accordance with the stored travel times.
13. The system of claim 9 , wherein the identifying the predicted route comprises using a Markov model.
A route prediction system for autonomous vehicles or navigation devices identifies a predicted route for a vehicle based on historical route data. The system collects and analyzes past route data, including vehicle positions, timestamps, and environmental conditions, to determine patterns and likely future routes. A Markov model is used to model the probabilities of transitions between different route segments, allowing the system to predict the most probable route the vehicle will take based on its current position and historical behavior. The system may also incorporate real-time data, such as traffic conditions or road closures, to refine the prediction. The predicted route is then used to optimize navigation, improve fuel efficiency, or enhance autonomous driving decisions. The Markov model enables probabilistic route prediction by considering the likelihood of different path transitions, improving accuracy over deterministic methods. The system may also include a data processing module to preprocess and store historical route data, ensuring efficient retrieval and analysis. The overall goal is to provide accurate, real-time route predictions to support autonomous driving or navigation assistance.
14. The system of claim 9 , wherein the operations further comprise, in response to a user selection of one of the results, causing display of an information box on a portion of the interface that is presenting the results, the information box including information for the selected one of the results.
User interface display and selection system. This invention addresses the need for providing detailed information related to selected items within a presented list of results on a user interface. The system includes components for presenting a plurality of results to a user and for receiving user input to select one of these results. In response to the user's selection, the system is configured to cause the display of an information box. This information box is positioned on a portion of the user interface that is currently displaying the results. The information box contains specific details pertaining to the particular result that was selected by the user. This allows users to quickly access relevant information for individual items from a list without navigating away from the current display.
15. The system of claim 9 , wherein the operations further comprise based on the predicted route, pre-fetching content likely to be retrieved by a user of the mobile computing device in a subsequent search.
A system for mobile computing devices predicts a user's route and pre-fetches content likely to be retrieved in future searches. The system addresses the problem of slow search response times and high data usage when users request information while on the move. By anticipating a user's location and likely search queries, the system proactively retrieves relevant content before it is explicitly requested, improving efficiency and reducing latency. The system first determines the user's current location and movement patterns using sensors and historical data. It then predicts the user's future route by analyzing these inputs. Based on the predicted route, the system identifies content that the user is likely to search for at upcoming locations, such as local business information, navigation directions, or event details. This content is pre-fetched and stored locally on the device, allowing for faster retrieval when the user performs a search. The system may also prioritize pre-fetching based on factors like network conditions, device storage, and the user's search history. By pre-fetching content in advance, the system reduces the need for real-time data requests, conserving bandwidth and improving search performance. The system is particularly useful for users who frequently search for location-based information while traveling.
16. A method comprising: detecting partial entry of a search query at the mobile computing device; accessing a location history of the mobile computing device; identifying a predicted route of the mobile computing device based in part on the location history; based on the location history, the predicted route, and the partial entry, determining a suggestion comprising one or more auto-complete search terms that complete the partial entry of the search query, the suggestion including a location along the predicted route; causing presentation of the suggestion that includes the location to complete the partial entry of the search query on the mobile computing device; causing a search to be performed based on the search query including the location along the predicted route; determining a speed of the mobile computing device based on the accessed location history; determining that the speed of the mobile computing device transgresses a threshold that indicates that a user of the mobile computing device is traveling on a highway; in response to determining that the speed transgresses the threshold, prioritizing results of the search that are associated with one or more exits on the highway; and causing display of an interface at the mobile computing device that presents the results of the search based on the search query.
17. The method of claim 16 , wherein the location along the predicted route comprises a predicted destination of the mobile computing device.
18. The method of claim 16 , wherein the identifying the predicted route comprises: accessing stored travel information of the mobile computing device between different locations in a geographic region; identifying one or more destination elements in the geographic region using the stored travel information; and determining probabilities that the one or more destination elements are a future location of the mobile computing device, wherein the identifying the predicted route of the mobile computing device is based at least on the probabilities.
19. The method of claim 16 , further comprising, in response to a user selection of one of the results, causing display of an information box on a portion of the interface that is presenting the results, the information box including information for the selected one of the results.
20. The method of claim 16 , further comprising based on the predicted route, pre-fetching content likely to be retrieved by a user of the mobile computing device in a subsequent search.
Unknown
March 2, 2021
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